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This is a proof of concept video for learning high-level tasks from non-expert human demonstrations. Since I am focusing on task-level learning, the robot has a set of known behaviors and the goal for the demonstrator is to teach the robot a new task that is not known a priori using these behaviors. In this particular case, the demonstrator demonstrates the facilitation of a group activity using an activity simulator that models the social robot, the users, and the activity itself. Namely, the demonstrator uses voice commands (CMU Speech Recognition) to control the behaviors of the simulated robot during the game. The mapping between the activity states and the robot’s behaviors are then learned from the demonstrations using a random forest based activity learning system.

Video for Publication: W.G. Louie and G. Nejat “A Persuasive Learning from Demonstration System Architecture for Social Group Recreational Activities,” IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 808-814, 2016.